Plants are living information‐processing organisms with highly adaptive behavior, allowing them to prosper in a harsh and fluctuating environment in spite of being sessile. Lacking a central nervous system, plants are distributed systems orchestrating complex computational processes performed at the tissue level. Here I consider plant tropisms as a useful input–output system boasting a robust mathematical description, naturally permitting a dialogue between mathematical modeling and biological observations. I propose tropisms as an ideal framework for the study of plant computational processes, allowing us to infer the relationship between observed tropic responses and known stimuli. I concentrate on macroscopic models, and elucidate this approach by presenting recent examples focusing on computational processes involved at different hierarchical levels of interactions: a plant's interaction with itself and its internal state, with the abiotic environment, and with neighboring plants.

中文翻译：

---

植物向性作为植物计算过程的窗口

植物是具有高度适应性的生物，是信息处理生物，尽管它们固执地存在，但它们仍可在恶劣而多变的环境中繁荣发展。缺乏中枢神经系统，植物是在组织水平上协调复杂计算过程的分布式系统。在这里，我认为植物的向性是一个有用的输入-输出系统，拥有强大的数学描述，自然而然地可以在数学建模和生物学观察之间进行对话。我建议将向性性作为研究植物计算过程的理想框架，从而使我们能够推断观察到的向性反应与已知刺激之间的关系。我专注于宏观模型，